The exemplary embodiment relates to the imaging arts. It finds particular application in connection with a print job simulator which provides a representation of a print job prior to printing.
Image non-uniformity occurs in the output images of digital image rendering devices, such as copiers, scanners, and printers, for a variety of reasons. Even relatively small non-uniformities can give rise to visibly objectionable print defects. In printing systems, physical alignments, component tolerances, wear and component age can influence the uniformity with which colorants, such as inks and toners, are laid down across the surface of print media. Streaks, for example, are one-dimensional image defects that generally run parallel to the process direction in the printed image. They can arise from non-uniform responses of the subsystems of an image rendering device, such as a xerographic marking engine, and can be constant over time in that they appear in relatively the same location from print to print. Photoreceptor scratches, contamination of the charger wire, non-uniform LED imager output and Raster Output Scanner (ROS) spot size variations, and spatially varying pressure on a bias transfer roll are examples of subsystem defects which can give rise to rendered image streaking in a xerographic marking engine. Bands are also one-dimensional image defects that generally run perpendicular to the process direction in a printed image. They are typically caused by time-varying performance of a marking engine subsystem, such as non-uniform velocity of the photoreceptor drive, out-of-roundness of development rolls, and wobble of the ROS polygon mirror. In a uniform patch of gray, streaks and bands may appear as a variation in the gray level. In general, “gray” refers to the optical density or area coverage value of any single color separation layer, whether the colorant is black, cyan, magenta, yellow, or some other color.
There are various approaches for detecting such defects. For example, test images designed to highlight any problems are rendered by an image rendering device, such as a printer, and captured by an image capturing device, such as a camera, a scanner, or the like. The captured images are compared with a standard test page designed to provide information about the performance of the printer. The existence of an artifact or defect in the image can thereby be detected. The customer or service representative uses the documents to diagnose printer problems, but generally only when the customer is already aware of a problem.
Various methods exist for correcting image quality defects, once they are detected. These include modification of the tone reproduction curves (TRCs) used in converting the original image data into machine-dependent image data. Automated systems have been developed for compensating for non-linearities introduced by an individual image rendering device. One such method involves providing a color sensor inside each image rendering device. The embedded color sensor is used to measure the color characteristics of the color marking device by measuring the color characteristics of an outputted color patch pattern. Feedback information about the color characteristics of the outputted color patch pattern is then input to a multi-dimensional look-up table for the image rendering device to improve the color reproduction.
However, even with such techniques available, image rendering devices can produce images which have noticeable defects. When a sizeable print job is to be printed, a customer may test print a few pages to ensure that the device chosen for rendering is performing satisfactorily. This process can be time consuming and also wastes supplies if the customer decides to check several image rendering devices before printing the job.